Day 11

Day 11 from #30dataChartChallenge

librarian::shelf(
  tidyverse
  , PeruData
  , lubridate
  , ggalt
  , cowplot
)

type_e <- c("Solar", "Eólica", "Termoeléctrica" , "Hidroeléctrica")
names(type_e) <- c(
  "#fcad02"
  , "#02a5e5"
  , "#e54202"
  , "#203387"
  )

gen <-
  PeruData::coes("generacion", start = "2021-01-01", end = "2021-12-31") |> 
  select(!2:3) |> 
  mutate(
    fecha = dmy(fecha)
    , tipo = str_to_sentence(tipo_generacion)
    , sem = week(fecha)
  ) |> 
  select(!1:2) |> 
  group_by(sem, tipo) |> 
  summarise(total = sum(total)) |> 
  ungroup() |> 
  mutate(
    tipo = factor(tipo, type_e)
  )

m_c <- "gray"

main_theme <- function(...){
  
  
  # t <- 
    theme_void() +
    theme(
      panel.grid.minor = element_blank()
      , panel.grid.major.x = element_blank()
      , axis.text = element_blank()
      , panel.background = element_blank()
      , plot.background = element_blank()
      , legend.position = "none"
    ) +
    theme(...)
  # t
}

p1 <- 
  gen |> 
  ggplot() +
  aes(sem, total, group = tipo, fill = tipo) +
  geom_col(
    # position = "dodge"
  ) +
  coord_polar() +
  scale_fill_manual(
    values = names(type_e)
  ) +
  main_theme(
    panel.grid.major.x = element_line(color = "grey60")
    , axis.text.x = element_text(color = "black", hjust = 1)
  )

p2 <- 
  gen |> 
  pivot_wider(names_from = tipo, values_from = total) |> 
  mutate(
    across(2:5, lag)
  ) |> 
  pivot_longer(!sem, names_to = "tipo") |> 
  left_join(gen) |> 
  drop_na() |> 
  mutate(
    cre = ((total - value) / value ) * 100
    , tipo = factor(tipo, c("Eólica", "Solar","Hidroeléctrica" ,"Termoeléctrica" ))
  ) |> 
  ggplot() +
  aes(sem, cre, group = tipo, color = tipo) +
  geom_hline(yintercept = 0, color = m_c, linetype = "dashed") +
  geom_hline(yintercept = -40, color = m_c, linetype = "dashed") +
  geom_hline(yintercept = 40, color = m_c, linetype = "dashed") +
  geom_vline(xintercept = 1, color = m_c, linetype = 4) +
  geom_xspline(size = 1) +
  ylim(-50, 50) +
  scale_x_continuous(breaks = seq(0, 50, by = 10)) +
  annotate("text", x = rep(1, 3), y = c(3, -37, 43), label = c("0%", "-40%", "40%"), vjust = 1) +
  coord_polar(start = 0) +
  scale_color_manual(values = names(type_e)) +
  main_theme(
    panel.grid.major.x = element_line(color = "grey60")
    , axis.text.x = element_text(color = "black", hjust = 1)
  )

lbl <- function(n = 1, x = 1.06, y = NULL, z = 18
    ){
  draw_label(
    label = type_e[n]
    , color = names(type_e)[n]
    , y = y
    , x = x
    , size = z
    , hjust = .5
    , fontface = "bold"
  )
}
  
p <- 
  ggdraw(xlim = c(0, 2), ylim = c(0, 1.2)) +
  draw_plot(p1) +
  draw_plot(p2, x = 1.1) +
  draw_label(
    "Perú - Generación eléctrica (semanal)"
    , x = 1.1
    , y = 1.1
    , size = 30
    , color = "#114468"
    , fontface = "bold"
  ) +
  draw_label(
    "Por tipo de generación"
    , x = 1.1
    , y = 1
    , size = 27
    , color = "#277f68"
  ) +
  lbl(1, y = .7) +
  lbl(2, y = .6) +
  lbl(3, y = .5) + 
  lbl(4, y = .4) +
  theme(
    plot.background = element_rect(
      "white", 
      color = NA
    )
  ) +
  draw_label(
    "Generación promedio"
    , x = .1
    , y = .97
    , size = 23
    , hjust = 0
    , color = "grey50"
  ) +
  draw_label(
    "Variación porcentual (%)"
    , x = 1.95
    , y = .97
    , size = 23
    , hjust = 1
    , color = "gray40"
  ) +
  draw_label(
    "#30DayChartChallenge | Data: COES - Perú | Day10: Circular | Viz: @JhonKevinFlore1"
    , x = 1
    , y = .05
    , color = "darkgrey"
  ) +
  draw_image(
    "https://raw.githubusercontent.com/TJhon/PeruData/main/figs/PeruData-night.png"
    , x = .96
    , y = -.28
    , width = .2
  )

ggsave(
  'plots/day11_dcc_22.png'
  , plot = p
  , height = 8
  , width = 16
)

knitr::include_graphics('https://raw.githubusercontent.com/TJhon/30DayChartChallenge/main/Plots/day11.png')